Statistical modelling of insect behavioural responses in relation to the chemical composition of test extracts

The use of generalized linear models (GLM) for relating changes in insect behaviour to changes in the chemical composition of a plant extract is presented and applied to data from an experimental study of the olfactory response of Cydia pomonella L. (Lepidoptera: Tortricidae) to apple volatiles. The volatiles were collected from healthy apples, artificially damaged apples or apples infested with C. pomonella larvae (either instar I, IV or V). These treatments produced a blend of 23 major components and the chemical composition of the blends differed substantially amongst the treatments. A statistically significant relationship was found between the concentration of hexyl hexanoate and 2-methylbutyl acetate in each extract and the number of moths moving upwind. Statistically significant models were developed which suggested that a relationship exists between the concentration of Z,E-alpha-farnesene, hexyl hexanoate and 2-methylbutyl acetate and the number and duration of movements made by the moths. Subsequently Y-tube assays were carried out to validate the predictions made with respect to the orientation of mated female C. pomonella. The results of these assays confirm hexyl hexanoate as an attractant. There were indications that 2-methylbutyl acetate acted as a repellent although differences were not statistically significant. Previous bioassays have shown that C. pomonella displays a statistically significant negative linear dose-response to alpha-farnesene (Hern & Dorn, 1999). The statistical methods employed are very flexible and fairly easy to implement, offering the potential to screen plant extracts for bioactive compounds with a minimum of biological constraints. Their general applicability has yet to be demonstrated and as such these analyses only offer evidence of statistical relationships; the results must be validated by additional bioassays before conclusions can be drawn.